CN110413884A - Apparatus, method, storage medium, and electronic device for providing online car-hailing service - Google Patents

Abstract

The present disclosure provides an online car-hailing service providing device, method, computer-readable storage medium, and electronic equipment. The device for providing online car-hailing services includes: a first acquisition unit, used to obtain the boarding location and the alighting location; a first estimation unit, used to obtain the estimated value of the first user's expected condition of the optional vehicle model; the second An acquiring unit, configured to acquire the setting value of the first user's expected condition; and a recommending unit, configured to recommend a car model that satisfies the set value of the first user's expected condition based on the estimated value of the first user's expected condition.

Description

Apparatus, method, storage medium, and electronic device for providing online car-hailing service

technical field

Embodiments of the present disclosure relate to an online car-hailing service providing device, method, computer-readable storage medium, and electronic equipment.

Background technique

Online car-hailing services refer to services that provide users with booking taxis or other types of vehicles through the Internet to help users travel. At present, there are more and more travel service providers on the market that provide online car-hailing services, and each travel service provider can provide multiple categories of car models. In this way, users can obtain a variety of online car-hailing services. The category of the vehicle indicates the type of the vehicle, for example, common categories may include taxi, economy, comfort, business, luxury, etc.

In order to provide more diversified travel services, a technical solution for aggregating the services of multiple travel service providers into one application software has been proposed. Through such a technical solution of aggregation mode, users can more conveniently compare and select the services of various travel service providers.

Contents of the invention

Embodiments of the present disclosure provide an online car-hailing service providing device, method, computer-readable storage medium, and electronic equipment capable of improving user experience.

An embodiment of the present disclosure provides an online car-hailing service providing device, the online car-hailing service providing device includes: a first acquisition unit, used to obtain the boarding location and alighting location; a first estimation unit, used to obtain The estimated value of the first user's expected condition of the optional vehicle type; the second acquisition unit is used to acquire the setting value of the first user's expected condition; and the recommendation unit is used to recommend based on the estimated value of the first user's expected condition A car model that satisfies the set value of the first user's expected condition.

An embodiment of the present disclosure provides a method for providing online car-hailing services. The method for providing online car-hailing services includes: obtaining the boarding location and the getting off location; obtaining the estimated value of the first user's expected condition of the optional vehicle model; obtaining The setting value of the first user's expected condition; and recommending a vehicle model that satisfies the set value of the first user's expected condition based on the estimated value of the first user's expected condition.

An embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored, and is characterized in that, when the program is executed by a processor, the above-mentioned steps in the method for providing an online car-hailing service are implemented.

An embodiment of the present disclosure provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. steps in the method.

According to the embodiments of the present disclosure, car models can be recommended according to the user's individual needs, thereby not only reducing the time and complexity for the user to select a car model, but also being closer to the real needs of the user and improving the user's experience.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings that need to be used in the description of the embodiments. The drawings in the following description are merely exemplary embodiments of the present disclosure.

Fig. 1 shows an example schematic diagram of an interface for providing online car-hailing services.

Fig. 2 is a schematic structural diagram showing an apparatus for providing a car-hailing service according to an embodiment of the present disclosure.

Fig. 3 is a schematic structural diagram showing an apparatus for providing a car-hailing service according to an embodiment of the present disclosure.

Fig. 4 is a schematic diagram illustrating the application of an expected condition prediction model according to an embodiment of the present disclosure.

Fig. 5A shows an exemplary schematic diagram of an application interface of an apparatus for providing a car-hailing service according to an embodiment of the present disclosure.

Fig. 5B shows an exemplary schematic diagram of another application interface of the car-hailing service providing device according to an embodiment of the present disclosure.

Fig. 6 is a flowchart illustrating a method for providing an online car-hailing service according to an embodiment of the present disclosure.

Fig. 7 is a schematic structural diagram showing an electronic device for providing online car-hailing service according to an embodiment of the present disclosure.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present disclosure more apparent, exemplary embodiments according to the present disclosure will be described in detail below with reference to the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure, and it should be understood that the present disclosure is not limited by the exemplary embodiments described here.

In this specification and the drawings, substantially the same or similar steps and elements are denoted by the same or similar reference numerals, and repeated descriptions of these steps and elements will be omitted. Meanwhile, in the description of the present disclosure, the terms "first", "second" and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance or ranking.

Fig. 1 shows an example schematic diagram of an interface 100 for providing online car-hailing services.

Referring to FIG. 1 , it is an interface 100 of an online car-hailing service provision solution in an aggregation mode. The interface 100 includes a map area 101 , an optional car model area 102 , and a taxi confirmation key 103 . The map area 101 displays a map related to the current trip, which may include the start point and end point of the trip, and the user can input or change the start point and end point of the trip through interaction. The optional vehicle model area 102 may include a plurality of vehicle category tags, and FIG. 1 exemplarily shows five category tags of taxi, economy type, comfortable type, business type, and luxury type. Each category label can include multiple optional travel service providers and corresponding estimated service prices. Figure 1 shows three travel service providers A, B and C under the economy category and the estimated service fees X yuan, Y yuan and Z yuan of the economy vehicles of these travel service providers.

Based on the information provided on the interface 100, the user can select the car models provided by one or more travel service providers under one or more vehicle category labels, for example, by clicking on the corresponding travel service provider under the corresponding category label. Travel service provider A and travel service provider B under the economy category in Figure 1 are selected. The car models selected at the same time can belong to the same or different categories. After the user has selected a car model, he can click the confirmation button 103 for calling a taxi, such as "Take a taxi now" in the figure, to call the online car-hailing service. Therefore, the online car-hailing service provision scheme in the aggregation mode can provide the online car-hailing service of the car model selected by the user as above.

However, as more and more travel service providers and vehicle categories can be accessed in the interface 100 , and vehicle model information becomes more and more scattered, it becomes more and more difficult for users to browse and select numerous vehicle models. For example, on the interface 100, users cannot directly express their needs for time cost and fare cost, but can only frequently switch category labels to browse and select models one by one. The operation process will become long and cumbersome, resulting in poor user experience .

To address one or more of the above problems, embodiments of the present disclosure provide an online car-hailing service providing device and a network car-hailing service providing method that can improve user experience.

It should be noted that although some embodiments of the present disclosure are described based on the network car-hailing service provision scheme of the aggregation mode, those skilled in the art can determine that the present disclosure is not limited to the network car-hailing service provision scheme of the aggregation mode , which can also be applied to other modes of online car-hailing service provision solutions, for example, a non-aggregated model that only provides a single travel service provider but provides multiple vehicle categories, or provides multiple travel service providers without distinguishing vehicle categories mode.

Fig. 2 is a schematic structural diagram showing an apparatus 200 for providing a car-hailing service according to an embodiment of the present disclosure.

Referring to FIG. 2 , the online car-hailing service provider 200 may include a first acquisition unit 201 , a first estimation unit 202 , a second acquisition unit 203 and a recommendation unit 204 . The first acquiring unit 201 is used to acquire the boarding location and the getting off location. The first estimation unit 202 is configured to obtain an estimated value of a first user's expected condition of an optional vehicle type. The second acquiring unit 203 is configured to acquire the setting value of the first user's expected condition. The recommending unit 204 is configured to recommend, based on the estimated value of the first user's expected condition, a car model that satisfies the set value of the first user's expected condition.

The online car-hailing service providing device 200 may be any device capable of providing online car-hailing services to users, such as smart phones, tablet computers, personal digital assistants and other devices. The online car-hailing service provider 200 according to the embodiment of the present disclosure can recommend car models to the user according to the pick-up location and drop-off location and other conditions (user expected conditions) provided by the user.

The first acquiring unit 201 can acquire the boarding location and the getting off location according to the user's input, for example, the user can input the boarding location and the getting off location by text, or select the boarding location and the getting off location from the map. In addition, the first acquisition unit 201 can also acquire the boarding location and the disembarking location by other means, for example, the user's current location can be obtained as the boarding location through a positioning system (for example, the Global Positioning System (GPS) or the Beidou positioning system) , Obtain the drop-off location by receiving location sharing sent by friends.

The optional car models according to the embodiments of the present disclosure represent the car models that users can choose for this service. For example, the online car-hailing service provider 200 can determine the optional car models that can provide this service after obtaining the pick-up location and the drop-off location. As the car model that the user can choose. In the embodiment of the present disclosure, "model" means the sum of the attributes distinguishing vehicles in the online car-hailing service providing device 200 . For example, in the online car-hailing service in the aggregation mode shown in Figure 1 above, the attributes that distinguish vehicles are "vehicle category" and "travel service provider", and "model" is the superposition of these two attributes. For example, for a vehicle whose vehicle category is "economy" and travel service provider A, its model is the travel service provider A's economy vehicle. In some embodiments, the "model" may also include more information, for example, it may also include a specific model of the vehicle, such as "new energy". For example, the "model" can be an economical new energy vehicle of travel service provider A. In the non-aggregated online car-hailing service, the "model" may only include the attributes of "vehicle category", such as "economical", "luxury", etc., or it may further include specific models, such as "economical new energy "vehicle. The present disclosure does not limit the specific form of the "vehicle type", as long as the vehicle can be distinguished in the online car-hailing service providing device 200 .

For optional car models, the first estimation unit 202 of the online car-hailing service provider 200 acquires the estimated value of the first user's expected condition. In this disclosure, the user's expected condition means the user's expected condition for this trip, for example, it may include: expected boarding time, expected getting off time, expected en route time, expected cost, expected service satisfaction or any combination of the above . Apparently, any other applicable expected conditions may also be adopted in the embodiment of the present disclosure. The estimated value of the user's expected condition represents the estimated value that the vehicle provided by the online car-hailing service provider device can achieve for the user's expected condition. For example, when the first user's expected condition is the expected boarding time, the estimated value is The estimated value of the expected boarding time that the vehicle provided by the car-hailing service providing device can achieve, that is, the estimated boarding time; when the first user's expected condition is the expected cost, the estimated value is the The estimated value of the expected cost that the vehicle can achieve, that is, the estimated cost. According to an embodiment of the present disclosure, the first estimation unit 202 may calculate the estimated value of the first user's expected condition by itself, or obtain the estimated value of the first user's expected condition from the server, that is, the server calculates the estimated value of the first user's expected condition The estimated value of the condition is then sent to the first estimation unit 202 of the online car-hailing service providing device 200, which all belong to the scope of "obtaining the estimated value of the first user's expected condition". The online car-hailing service providing device 200 may be connected to a server through a communication device to obtain the above estimated value.

The estimated value of the first user's expected condition can be calculated based on factors such as target vehicle type, user characteristics, current supply and demand characteristics, space-time characteristics and/or current order characteristics. For example, when the first user's expected condition is the expected boarding time, the first estimation unit 202 or the server can calculate the shortest time that each optional vehicle model is expected to arrive at the boarding location as the expected boarding time of each optional vehicle model. Estimated value of expected conditions. When calculating the shortest time for a car model to arrive at the boarding location, for example, you can consider: the car model for the current calculation, that is, the target model; user characteristics, for example, for old users, priority can be dispatched, so that the boarding time can be earlier; current supply and demand characteristics , for example, when the current demand is strong, the expected boarding time may be later; spatio-temporal characteristics, for example, the expected boarding time may be later at remote boarding locations or drop-off locations, and the expected boarding time may be later at night; The characteristics of the current order, for example, if the current order is attached with a red envelope, the expected boarding time may be shortened. When calculating the estimated value of the user's expected condition, the above-mentioned factors can be used as input parameters of the estimation model, and the output of the estimation model is an estimated value. The prediction model can be established, for example, by artificial intelligence machine learning technology (such as XGBoost model), for example, the prediction model can be trained by using the sample data of a period of time in the past as the training data, thereby generating the data that can be used to generate the user's expected conditions. Estimation model for estimated values. In some embodiments of the present disclosure, the estimation model for calculating the estimated value may also be a simple calculation formula instead of a trained artificial intelligence model. For example, if the expected cost is the first user's expected condition, then the expected cost The estimated value can be obtained simply by multiplying the unit price by the mileage of the itinerary instead of the artificial intelligence model. Of course, it can also be calculated by the aforementioned AI-based estimation model. In an embodiment of the present disclosure, the estimated value of the first user's expected condition can be obtained from the estimated interface provided by the travel service provider, that is, the server of the travel service provider provides the corresponding estimated value to the online car-hailing service provider 200 The first estimation unit 202 of . The server of the travel service provider can calculate the estimated value based on the above-mentioned various estimation models.

According to an embodiment of the present disclosure, the estimated value of the first user's expected condition acquired by the first estimation unit 202 can be used for comparison with the set value of the first user's expected condition input by the user, so that the online car-hailing service providing device 200 The recommendation unit 204 recommends car models that meet the set value of the first user expectation condition. The setting value of the user's expected condition indicates the value set by the user for the user's expected condition, and the user requires that the recommended vehicle model can meet the set value. For example, when the first user's expected condition is the expected boarding time, the set value is the time required to get on the bus set by the user; when the first user's expected condition is the expected fee, the set value is the required fee set by the user . The second acquiring unit 203 is configured to acquire the setting value of the first user's expected condition. The setting value may be a value currently input by the user, or a setting value stored by the user in the online car-hailing service providing apparatus 200 for multiple use. There are various ways for the user to input the setting value, including but not limited to voice input, handwriting input, pinyin input, etc. Moreover, the user can not only input the value directly, but also input by graphical operation methods such as dragging the progress bar. The setting value of the first user's expected condition can be not only a point value but also a range value, for example, the user's expected boarding time or the minimum and maximum value of the expected cost can be set.

After the second acquiring unit 203 acquires the set value of the first user's expected condition, the recommending unit 204 can compare the estimated value of the first user's expected condition of each optional vehicle type with the set value, so as to recommend a vehicle type that satisfies the set value . The recommended car models can be displayed on the interface of the online car-hailing service providing device 200 for users to choose. The user can select all recommended car models, that is, make a car call without further selection of the recommended car models. Optionally, the user may also select some car models from the recommended car models to make a call. For example, the estimated value display unit 307 can recommend car models by automatically checking car models that meet the set value on the user interface. Further, the user can make further selections by manually adjusting the checked car models, for example, the user can reduce the car models by removing the check.

According to an embodiment of the present disclosure, the first user expectation condition may include a plurality of conditions, and the recommending unit recommends multiple conditions simultaneously satisfying the first user expectation condition based on estimated values of the plurality of conditions of the first user expectation condition. The model of the setting value of each condition. For example, when the first user's expected condition includes both the expected fare and the expected boarding time, the first estimation unit 202 acquires the estimated values of the expected boarding time and the expected boarding time corresponding to each optional vehicle type. The second obtaining unit 203 obtains the setting values of the user's expected boarding time and expected fare. Therefore, the recommending unit 204 recommends to the user a car model that satisfies both the set values of expected boarding time and expected cost. In this embodiment, both the expected cost and the expected boarding time belong to the first user's expected condition, and the acquisition of the estimated value and the set value of the two are logically independent, and the model recommendation is based on the expected cost and the expected boarding time at the same time both.

It should be noted that the order and times of execution of the first estimation unit 202 and the second acquisition unit 203 of the online car-hailing service providing apparatus 200 in the embodiment of the present disclosure are not limited. For example, the first estimation unit 202 may execute the acquisition of the estimated value first, or the second acquisition unit 203 may first execute the acquisition of the set value, or both may even be executed in parallel. It is also possible that the first estimation unit 202 acquires an estimated value first, and then acquires an estimated value after the second acquisition unit 203 acquires the set value to acquire a more accurate estimated value.

According to the embodiment of the present disclosure, the online car-hailing service provider 200 can recommend car models based on the setting values of the expected conditions input by the user, that is, according to the user's individual needs, which can not only reduce the time and cumbersomeness of the user's choice of car models, but also can It is closer to the real needs of users and improves the user experience. For example, users can directly express their needs for time cost and/or economic cost by setting the expected time range for boarding and/or the expected cost range, without frequently switching category labels to select the desired model.

The online car-hailing service providing device 200 according to the embodiment of the present disclosure can execute the functions corresponding to the relevant modules through the central processing unit and/or the image processing unit in conjunction with the corresponding computer program code, and can adopt various appropriate operating systems, such as An Android (Android) system, a Linux system, a Unix system, or a Windows (Windows) system, etc., are not limited in the embodiments of the present disclosure.

Fig. 3 is a schematic structural diagram showing an apparatus 300 for providing an online car-hailing service according to an embodiment of the present disclosure.

In addition to the first acquisition unit 301, the first estimation unit 302, the second acquisition unit 204 corresponding to the first acquisition unit 201, the first estimation unit 202, the second acquisition unit 203, and the recommendation unit 204, The unit 303 and the recommendation unit 304 further include one or more of the following units: a third acquisition unit 305 , a second estimation unit 306 , an estimated value display unit 307 , and a default value setting unit 308 . For the description of the first acquisition unit 301 , the first estimation unit 302 , the second acquisition unit 303 and the recommendation unit 304 , refer to the above description for FIG. 2 .

In some embodiments of the present disclosure, the online car-hailing service providing apparatus 300 includes a third acquisition unit 305, configured to acquire the user's change operation on the recommended car model. After the recommendation unit 304 recommends expected car models to the user, the user can manually adjust the recommended car models according to preferences, for example, the user can increase or decrease car models based on the recommended car models. The online car-hailing service providing device 300 can provide the user with an interface for the user to check the car models, so that the user can make a selection on the interface, for example, the recommended car models can be reduced by removing the selection, or the unrecommended car models can be selected by checking the unrecommended car models. Add models. The third acquiring unit 305 may acquire the user's change operation on the recommended car model to obtain information on the changed car model. By providing the user with the option to change the car model, the user's flexibility in choosing the car model can be improved.

In some embodiments of the present disclosure, the online car-hailing service providing device 300 includes a second estimation unit 306 and an estimation value display unit 307 . The second estimating unit 306 is used to acquire the estimated value of the second user's expected condition of the recommended car model or the car model after the user changes the recommended car model. The estimated value display unit 307 is configured to display the estimated value of the second user's expected condition and/or its range. If the user does not make any changes to the recommended car model, the second estimation unit 306 can obtain the estimated value of the second user's expected condition of the recommended car model, wherein the second user's expected condition can be the same as the first user's expected condition The conditions are different. For example, when the first user expected condition is expected boarding time, the second user expected condition may be expected fare. Therefore, after the online car-hailing service provider 300 recommends a car model that satisfies the set value of the user's expected boarding time based on the estimated value of the expected boarding time, the second estimation unit 306 of the online car-hailing service providing device 300 can obtain The recommended estimated value of the expected cost of each vehicle type, and then the estimated value display unit 307 may display to the user the estimated value and/or estimated value of the expected cost of the recommended vehicle type that meets the user's expected boarding time. scope. For example, for displaying the expected cost, the expected cost of the vehicle type may be displayed on the user interface at a position corresponding to the corresponding vehicle type. For the display of the range of the expected cost, the range of the expected cost of these models can be displayed at any suitable position on the user interface (for example, next to the taxi confirmation key), assuming that the cost estimate of the model with the highest expected cost among the recommended models The value is 50 yuan, and the estimated cost of the model with the lowest cost is 30 yuan, then the expected cost displayed by the estimated value display unit 307 to the user is in the range of 30-50 yuan. If the user changes the recommended car model, for example, as mentioned above, the recommended car model is increased or decreased by ticking on the interface, the second estimation unit 306 can obtain the information after the user changes the recommended car model. The estimated value of the second user's expected condition of the car model, the estimated value display unit 307 can display to the user the estimated value and/or the range of the estimated value of the second user's expected condition of the changed car model, specifically displaying The method is similar to the display method when the vehicle model does not change.

When the estimated value display unit 307 shows the range of the estimated value of the second user's expected condition to the user, the user can predict that the second user's expected value will be determined when he takes a taxi according to the model recommended by the first user's expected condition or the changed model. The estimated value of the condition and/or its range, so that it can be judged whether the estimated value of the expected condition of the second user exceeds his expectation. Then, the user can decide whether to call the vehicle according to the current model. For example, if the user thinks that the estimated value range of the second user's expected condition exceeds his expectations, he can further modify the setting value of the first user's expected condition so as to obtain a newly recommended car model. For example, when the first user's expected condition is the expected boarding time and the second user's expected condition is the expected cost, assuming that the expected boarding time set by the user is 5 minutes, the expected car model recommended by the online car-hailing service providing device 300 If the range of the fee is 100-150 yuan, the user may find that the fees for the models that can be reached within 5 minutes of the expected boarding time are too high. Therefore, the user can change the set value of the expected boarding time, for example, to 10 minutes, so as to obtain a new recommended car model, for example, the expected cost of the new car model is in the range of 70-120 yuan. If the expected cost is in line with the user's expectations, the user can call a vehicle based on these vehicle types.

Furthermore, in some embodiments of the present disclosure, when the user knows the estimated value range of the second user's expected condition, the user may wish to further narrow the estimated value range, so as to obtain the second user's expected condition with a smaller Recommendations for models in the estimated value range. For example, in the example where the first user's expected condition is the expected boarding time and the second user's expected condition is the expected fee, the user may hope that the fee is less than 100 yuan, or that the fee is between 80-100 yuan. Next, the user can further set the setting value of the expected fee, for example, 100 yuan, which means that the fee does not exceed 100 yuan, or 80-100 yuan, which means that the fee is between 80-100 yuan. Based on this, the online car-hailing service provider 300 Re-recommend models to obtain a model that meets both the expected boarding time and the expected cost. Therefore, the second acquiring unit 303 of the online car-hailing service providing device 300 can also acquire the setting value of the second user's expected condition, and the recommending unit 304 can also based on the estimated value of the first user's expected condition and the value of the second user's expected condition The estimated value recommends a car model that satisfies both the set value of the first user's expected condition and the set value of the second user's expected condition.

In addition, according to some embodiments of the present disclosure, the online car-hailing service providing device 300 may further include a default value setting unit 308, which is used for setting and displaying the estimated value of the first user's expected condition based on the optional vehicle type. A default value for the setting value of the user's expected condition. Thus, the setting value of the first user's expected condition can be suggested to the user, and if the user approves the default value, the recommended vehicle type can be obtained without inputting, thereby speeding up the taxi-hailing process. For example, when the first user's expected condition is the expected boarding time, the first estimation unit 303 may obtain that the shortest time for all optional vehicles to reach the user's boarding location is 10 minutes, then the default value setting unit 308 may Set the default value of the set value of the user's expected boarding time to 10 minutes, or set the minimum value of the range of the default value of the expected boarding time to 10 minutes, and display the default value on the interface, to suggest to the user. In this way, it is convenient for the user to know the minimum waiting time when using the online car-hailing service providing device 300 , and it is convenient for the user to set the setting value of the expected boarding time.

It should be noted that, in the embodiment of the online car-hailing service providing device 300, the acquisition or calculation of the second user's expected condition is similar to the first user's expected condition. Factors such as supply and demand characteristics, spatiotemporal characteristics, and/or current order characteristics are estimated based on an estimation model trained with training data.

Fig. 4 shows a schematic diagram of application of an expected condition prediction model according to an embodiment of the present disclosure.

Referring to FIG. 4 , after the training of the prediction model corresponding to the expected condition is completed, relevant parameters can be input into the prediction model, so as to obtain the output of the prediction model as the predicted value corresponding to the expected condition. Figure 4 shows the first expected condition prediction model and the second expected condition prediction model. It should be noted that these two models are independent, that is, the first The forecasting model of the expected condition is used to call the forecasting model of the second expected condition when calculating the estimated value of the second expected condition. The input of the first expected condition prediction model and the input of the second expected condition prediction model may be the same or different. The model input in FIG. 4 exemplarily shows the target car model, supply and demand characteristics, order characteristics, and user characteristics, but the model input is not limited to those shown, and may also include other inputs, specifically determined according to the nature of specific expected conditions.

Machine learning techniques can be used to train sample data (for example, the sample data of the latest month) to establish a prediction model. The construction of the sample data can be based on the real order receiving time, order quantity, vehicle travel time, actual fare and other related data of each model in the historical order. According to the embodiment of the present disclosure, the XGBoost model can be used, and the XGBoost model includes a scalable, portable and distributable gradient boosting (Gradient Boosting) library. Compared with other gradient boosting models, XGBoost can calculate faster speed to get more accurate estimates. Of course, the embodiments of the present disclosure may also use various other machine learning models to calculate the estimated value, for example, an Adaboost model or a decision tree model.

Embodiments of the present disclosure will be further described below in combination with an example of an application interface. FIG. 5A and FIG. 5B show an exemplary schematic diagram of an application interface 500 of an apparatus for providing a car-hailing service according to an embodiment of the present disclosure. In the embodiment shown in FIG. 5A and FIG. 5B , the first user expectation condition is the expected boarding time, and the second user expectation condition is the expected cost. Referring to FIG. 5A , the interface 500 includes a map area 501 , a boarding time setting area 502 , a recommended vehicle type display area 503 , an estimated cost range display area 504 , and a taxi confirmation key 505 .

The map area 501 displays a map related to the current trip, which may include the start point and end point of the trip. The user can input the boarding location and alighting location through text, or select the boarding location and alighting location from the map, so that the first acquisition unit of the online car-hailing service provider can obtain the boarding location and alighting location according to the user's input. Place.

The boarding time setting area 502 is used for the user to set the setting value of the expected boarding time, so that the second acquisition unit of the online car-hailing service provider can obtain the setting value of the expected boarding time as the first user's expected condition. For example, as shown in the figure, the user can respectively set the minimum time and maximum time expected to board the vehicle by dragging the progress bar in the setting area 502 . The minimum time shown in FIG. 5A is 5 minutes, and the maximum time is 10 minutes, that is, the expected boarding time set by the user is 5-10 minutes. In addition, the estimation unit of the online car-hailing service providing device can obtain the estimated value of the expected boarding time that can be achieved by each optional vehicle model, that is, the estimated value of the expected condition of the first user. As mentioned above, the first estimation unit can calculate the estimated value of the expected boarding time by itself, or obtain the estimated value of the expected boarding time from the server, that is, the server calculates the estimated value of the expected boarding time and sends it to the network. The first estimation unit of the car-hailing service providing device.

Then, the recommendation unit of the online car-hailing service provider device can recommend a car model that satisfies the set value of the expected boarding time based on the estimated value of the expected boarding time of each optional model. The recommended vehicle type display area 503 is used to display the vehicle type recommended by the online car-hailing service provider according to the expected boarding time set by the user. In Figure 5A, the vehicle models recommended by the online car-hailing service provider are two models of travel service provider A and travel service provider B under the economical model. Displayed with "√". The recommended car model display area 503 also displays the estimated value of the expected cost (the second user expected condition) of the corresponding car model at each recommended car model, that is, the "estimated cost" in the figure. As mentioned above, the estimated value of the expected cost as the expected condition of the second user can be obtained by the second estimation unit of the online car-hailing service provider.

In addition, in this embodiment, the estimated cost range display area 504 displays the range of the estimated value of the expected cost as the second user's expected condition. In the example in FIG. 5A , among all the recommended car models, the estimated minimum cost is M yuan, and the estimated highest cost is N yuan. Through this information, the user can intuitively determine whether the estimated fare can meet the psychological expectation. When the estimated fare meets the user's psychological expectation, he can click the taxi confirmation button 505 (that is, "hit a taxi now" in the figure) to make a vehicle call.

When the user finds that the estimated fare does not meet their psychological expectations, the user can drag the progress bar to reset the set value of the expected boarding time, as shown in Figure 5B, the user can set the expected boarding time to 5 to 20 minutes. The recommendation unit of the online car-hailing service provider re-recommends the car model according to the new setting value. The recommended car model display area 503 in Figure 5B shows that 5 car models and their estimated costs are recommended at this time, of which 3 car models belong to the economical model, and 2 car models belong to the comfortable model. Models of 3 travel service providers under the comfort category. For the other two car models, the user can, for example, use a sliding gesture to view them in the recommended car model display area 503 . In addition, according to the embodiment of the present disclosure, the above five car models can be displayed by categories. For example, when the economy category label is selected, 3 recommended models under the economy category are displayed; when the comfort category label is selected, 2 recommended models under the comfort category are displayed. According to an embodiment of the present disclosure, all five recommended car models may also be displayed on the interface at the same time. In addition, according to some embodiments of the present disclosure, the recommendation unit of the online car-hailing service provider can arrange the recommended car models according to the estimated cost (the estimated value of the second user's expected condition), for example, the car with a lower estimated cost The car models are arranged on the left, and when all the recommended car models cannot be displayed on the interface at the same time, the car models with lower estimated costs are displayed first, so that users can give priority to the models with lower estimated costs. According to other embodiments, the recommendation unit can also arrange the recommended car models according to the expected boarding time (the estimated value of the first user's expected condition), for example, the car models with the estimated expected boarding time are arranged closer to each other. Left, and when all the recommended car models cannot be displayed on the interface at the same time, the car models with the estimated short expected boarding time are displayed first, so that users can give priority to the models with the short expected boarding time.

In FIG. 5B , the estimated fare range display area 504 shows that the range of the estimated fares of the newly recommended five car models has changed from M' to N' yuan. If the user thinks that the range of the estimated fare at this time is in line with expectations, he can directly call the vehicle. Otherwise, the user can also check or uncheck the car models displayed in the recommended car model display area 503 to increase or decrease the range of calling vehicles. For this process, refer to the above description for the third acquisition unit.

It should be noted that although FIG. 5A and FIG. 5B illustrate the expected boarding time as the first user expectation condition, the embodiments of the present disclosure are not limited thereto. For example, the first user's expected condition can also be expected cost, expected arrival time, etc., so that corresponding display and interaction can be performed through a user interface similar to interface 500, for example, the expected cost, expected arrival time, etc. can be set through the progress bar value to set.

Compared with the interface 100 in FIG. 1 , the interface 500 in FIG. 5A and FIG. 5B allows the user to express individual needs more conveniently, so that the travel service required by the user can be provided to the user more efficiently.

FIG. 6 is a flow chart illustrating a method 600 for providing an online car-hailing service according to an embodiment of the present disclosure.

Referring to FIG. 6 , the online car-hailing service provision method 600 includes the following steps 601 to 604 . In step 601, the pick-up location and the drop-off location are acquired. In step 602, an estimated value of a first user's expected condition of an optional vehicle type is obtained. In step 603: acquiring the setting value of the first user's expected condition. In step 604: Recommending a car model that satisfies the set value of the first user's expected condition based on the estimated value of the first user's expected condition. For example, the online car-hailing service providing method 600 may be executed by any electronic device such as an online car-hailing service providing device. The above description about the device for providing online car-hailing service is also applicable to the method for providing online car-hailing service.

According to an embodiment of the present disclosure, the online car-hailing service providing method 600 may further include: receiving a user's change operation on the recommended car model.

According to an embodiment of the present disclosure, the online car-hailing service providing method 600 may further include: acquiring the recommended car model or the user's estimated value of the second user's expected condition of the car model after the recommended car model has been changed; and displaying the second user's expected condition Two ranges of estimated values of user expected conditions, wherein the first user expected condition is different from the second user expected condition.

According to an embodiment of the present disclosure, the online car-hailing service provision method 600 may further include: acquiring the setting value of the second user's expected condition; based on the estimated value of the first user's expected condition and the second user's expected condition The predicted value of is recommended to recommend a car model that satisfies both the setting value of the first user expectation condition and the setting value of the second user expectation condition.

According to an embodiment of the present disclosure, in the method 600 for providing online car-hailing services, car models are recommended by automatically checking car models that meet the set value on the user interface.

According to an embodiment of the present disclosure, in the online car-hailing service providing method 600, the first user expected condition includes multiple conditions, and based on the estimated value of the multiple conditions of the first user expected condition, it is recommended to satisfy all the conditions at the same time. The car model of the setting values of the plurality of conditions of the first user expected condition.

According to an embodiment of the present disclosure, in the online car-hailing service providing method 600, the setting value of the first user expected condition and/or the second user expected condition is acquired through a progress bar.

According to an embodiment of the present disclosure, in the online car-hailing service providing method 600, the recommended car models are arranged according to the estimated value of the first user's expected condition or the estimated value of the second user's expected condition.

According to an embodiment of the present disclosure, the online car-hailing service providing method 600 may further include: setting and displaying the default setting value of the first user's expected condition based on the estimated value of the first user's expected condition of the optional vehicle type value.

An embodiment of the present disclosure also provides a computer-readable storage medium storing computer-executable instructions, wherein, when the computer-executable instructions are executed by a processor, the online car-hailing service providing method of any one of the above-mentioned embodiments is performed.

The computer-readable storage medium may be any combination of one or more computer-readable storage media, for example, one computer-readable storage medium may contain a computer program for randomly generating a sequence of instructions for calculating an estimated value of a first user's expected condition For program code readable, another computer readable storage medium includes computer readable program code for calculating an estimate of a second user expected condition.

An embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. Steps in a method for providing a ride-hailing service.

Fig. 7 is a schematic structural diagram showing an electronic device 700 for providing online car-hailing service according to an embodiment of the present disclosure.

As shown in FIG. 7 , an electronic device 700 includes a processor (CPU) 701 that can execute various appropriate actions and processes according to programs stored or loaded in a memory 702 . The processor 701 and the memory 702 can be connected to each other through a bus 703 . According to an embodiment of the present disclosure, the electronic device 700 may further include an input/output (I/O) interface 704 , which may also be connected to the bus 703 .

According to embodiments of the present disclosure, the processes described above can also be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method of the process described above.

The online car-hailing service providing device, method, computer-readable storage medium, and electronic device of the embodiments of the present disclosure can recommend car models according to the individual needs of users, thereby not only reducing the time and tediousness for users to choose car models, but also enabling more Close to the real needs of users and improve user experience.

It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functions and operations of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logic devices for implementing the specified Executable instructions for a function. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.

In general, the various example embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, firmware, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be executed by a controller, microprocessor or other computing device. When aspects of the embodiments of the present disclosure are illustrated or described as block diagrams, flowcharts, or using some other graphical representation, it is to be understood that the blocks, devices, systems, techniques, or methods described herein may serve as non-limiting Examples are implemented in hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controllers or other computing devices, or some combination thereof.

The processor in the embodiment of the present disclosure may be an integrated circuit chip, which has a signal processing capability. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components. Various methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc., and may be of an X86 architecture or an ARM architecture.

A computer-readable storage medium in embodiments of the present disclosure can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The nonvolatile memory can be read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, many forms of RAM are available such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDR SDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Synchronous Linked Dynamic Random Access Memory (SLDRAM), and Direct Memory Bus Random Access Memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but not be limited to, these and any other suitable types of memory.

The exemplary embodiments of the present disclosure described in detail above are illustrative only and not restrictive. It should be understood by those skilled in the art that various modifications and combinations can be made to these embodiments or their features without departing from the principles and spirit of the present disclosure, and such modifications should fall within the scope of the present disclosure.

Claims (15)

1. a kind of net about vehicle service providing apparatus, comprising:

First acquisition unit, for obtaining Entrucking Point and place of getting off；

First estimates unit, the discreet value of first user's anticipated conditions for obtaining optional vehicle；

Second acquisition unit, for obtaining the setting value of the first user anticipated conditions；And

Recommendation unit meets the first user anticipated conditions for the discreet value recommendation based on the first user anticipated conditions Setting value vehicle.

2. net as described in claim 1 about vehicle service providing apparatus, further includes:

Third acquiring unit operates the change for the vehicle recommended for obtaining user.

3. net as claimed in claim 1 or 2 about vehicle service providing apparatus, further includes:

Second estimates unit, and second for obtaining the vehicle after recommended vehicle or user change the vehicle recommended is used The discreet value of family anticipated conditions；And

Discreet value display unit, for showing the discreet value and/or its range of the second user anticipated conditions.

4. net as claimed in claim 3 about vehicle service providing apparatus, wherein

The second acquisition unit is also used to obtain the setting value of the second user anticipated conditions, and

The recommendation unit is also used to discreet value and the second user anticipated conditions based on the first user anticipated conditions Discreet value recommend and meanwhile meet the setting value of the first user anticipated conditions and the setting of the second user anticipated conditions The vehicle of value.

5. net as described in claim 1 about vehicle service providing apparatus, wherein

The recommendation unit passes through chooses the vehicle for meeting the setting value in user interface progress vehicle recommendation automatically.

6. net as described in claim 1 about vehicle service providing apparatus, wherein

The first user anticipated conditions include multiple conditions, and

The discreet values of multiple conditions of the recommendation unit based on the first user anticipated conditions is recommended while meeting described the The vehicle of the setting value of multiple conditions of one user's anticipated conditions.

7. net as claimed in claim 3 about vehicle service providing apparatus, wherein

The second acquisition unit obtains the first user anticipated conditions and/or the expected item of the second user by progress bar The setting value of part.

8. net as claimed in claim 3 about vehicle service providing apparatus, wherein

The recommendation unit is according to the discreet value of the first user anticipated conditions or estimating for the second user anticipated conditions Value arranges recommended vehicle.

9. net as described in claim 1 about vehicle service providing apparatus, further includes:

Default value setup unit, discreet value setting and display institute for first user's anticipated conditions based on the optional vehicle State the default value of the setting value of first user's anticipated conditions.

10. net as described in claim 1 about vehicle service providing apparatus, wherein

The net about vehicle service providing apparatus provides the vehicle of multiple categories and/or multiple trip service providers.

11. a kind of net about vehicle service providing method, comprising:

Obtain Entrucking Point and place of getting off；

Obtain the discreet value of first user's anticipated conditions of optional vehicle；

Obtain the setting value of the first user anticipated conditions；And

The vehicle for meeting the setting value of the first user anticipated conditions is recommended in discreet value based on the first user anticipated conditions Type.

12. net as claimed in claim 11 about vehicle service providing method, further includes:

User is received to operate the change for the vehicle recommended.

13. the net about vehicle service providing method as described in claim 11 or 12, further includes:

Obtain estimating for the second user anticipated conditions of the vehicle after recommended vehicle or user change the vehicle recommended Value；And

Show the range of the discreet value of the second user anticipated conditions.

14. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor The step in the method as described in any one of claim 11-13 is realized when execution.

15. a kind of electronic equipment including memory, processor and stores the calculating that can be run on a memory and on a processor Machine program, which is characterized in that the step of the method as described in any one of claim 11-13 is realized when the processor executes Suddenly.